code: def cast_like(tensor1, tensor2):
      """Casts a tensor to the same dtype as another.
  
      Args:
          tensor1 (tensor_like): tensor to cast
          tensor2 (tensor_like): tensor with corresponding dtype to cast to
  
      Returns:
          tensor_like: a tensor with the same shape and values as ``tensor1`` and the
          same dtype as ``tensor2``
  
      **Example**
  
      >>> x = torch.tensor([1, 2])
      >>> y = torch.tensor([3., 4.])
      >>> cast_like(x, y)
      tensor([1., 2.])
      """
      if isinstance(tensor2, tuple) and len(tensor2) > 0:
          tensor2 = tensor2[0]
      if isinstance(tensor2, ArrayBox):
          dtype = ar.to_numpy(
              tensor2._value
          ).dtype.type  # pylint: disable=protected-access
      elif not is_abstract(tensor2):
          dtype = ar.to_numpy(tensor2).dtype.type
      else:
          dtype = tensor2.dtype
      return cast(tensor1, dtype)
  
file_path: pennylane/pennylane/math/utils.py
imports: import warnings
  import autoray
  import numpy
  from autograd.numpy.numpy_boxes import ArrayBox
  from autoray import numpy
  from .None import single_dispatch
label_desc: Use image node_id 4 for calling a global function with example usage: cast_like(tensor1, tensor2) and returns: cast